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Concerning the overwhelming advantages of solar energy, controlling and exploiting solar energy by using solar panels is one of the main fields of research in the domain of renewable energy. The choice of solar panel technology is highly significant to exploit as much energy as possible. In this paper, the main goal is to select the best technology for solar panels by investigating nine technologies from the first, second, and third generations of solar panels. Moreover, five sustainable criteria of electrical, mechanical, economic, technical, and climate, and 20 subcriteria are given for making decision analysis. Then, the best–worst method is employed according to the experts' opinions for weighting the criteria and for comparing the ranking of the solar energy technologies a framework based on the MULTIMOOSRAL multiple criteria decision‐making method is proposed. Finally, sensitivity analysis will be conducted on the ranking of the technologies. By exploiting the proposed methodology, CIS/CIGS and Perovskite Solar cell are ranked 1 and 2 as the best solar panel technologies for the selected locations. [ABSTRACT FROM AUTHOR]

While peer‐to‐peer (P2P) financing mechanisms have recently gained significant popularity, small and medium sized enterprise (SME) entrepreneurs still harbor a considerable degree of skepticism about the role of governments in promoting alternative supply chain finance (SCF) solutions in the re‐emergence of supply chain (SC) localization. This paper studies the SC financing problem of a capital‐constrained SME entrepreneur under two alternative financing schemes provided by an online P2P lending‐investment platform, namely debt financing (DF) and equity financing (EF). Considering the competition between a local and a foreign SC in a shared market, we investigate the direct (i.e., subsidizing domestic production) and indirect (i.e., subsidizing P2P platform service fee) roles of government intervention toward SC localization. Formulating a three‐level Stackelberg game model, this paper presents a scenario‐based decision‐making framework to jointly evaluate four different SCF scenarios through the lens of local SC, P2P financing platforms, and government. The results reveal that there exist three possible regions (i.e., DF, EF, and Conflict), within which the government and the P2P financing platforms can examine the alternative SCF schemes in order to achieve a mutually agreeable agreement. Our sensitivity analysis on interest rate and exchange ratio suggests that, when financed via an online P2P lending platform (i.e., DF), the local SC always achieves a higher profit under the direct intervention policy. The indirect policy, however, is preferred only when EF is the main source of SCF and the exchange ratio is sufficiently high. [ABSTRACT FROM AUTHOR]

In recent years, maintenance, especially its preventive type, has been seen as an effective and considerable factor in improving the functions of machines. Maintenance plays a vital role in organizations by keeping and increasing the reliability, accessibility, the quality of products, risk mitigation, return improvement, and safety. An effective maintenance programme can be realized by implementing a proper maintenance strategy. Therefore, maintenance and its strategies have a special status in industries. However, selecting a proper maintenance strategy has always been a complex process because maintenance is a nonrepetitive task. Likewise, the lack of failure records and constant changes in the conditions of machines makes it further complicated. Hence, the decision-making also depends on experts' opinions and because some kind of risk and uncertainty are always there in experts evaluations, the reliability of evaluations is questionable. The present study was aimed to develop a risk-based model grounded on the analytical hierarchical process, namely, RAHP, to meet this need of maintenance. A case study from a steel rolling company was considered to evaluate the effectiveness of this model. [ABSTRACT FROM AUTHOR]